Triple

T33369105
Position Surface form Disambiguated ID Type / Status
Subject Panzer Kaserne, Böblingen, Germany E854434 entity
Predicate hasPrimaryLanguageOfSurroundingArea P91957 FINISHED
Object German LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: German | Statement: [Panzer Kaserne, Böblingen, Germany, hasPrimaryLanguageOfSurroundingArea, German]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageOfSurroundingArea
Context triple: [Panzer Kaserne, Böblingen, Germany, hasPrimaryLanguageOfSurroundingArea, German]
  • A. hasPrimaryLanguageNearby chosen
    Indicates that an entity is associated with a primary language that is predominantly used or present in its immediate geographic or contextual vicinity.
  • B. hasOfficialLanguageOfSurroundingCountry
    Indicates that an entity uses as its official language the same language that is official in the country surrounding it.
  • C. hasSecondaryLanguageNearby
    Indicates that an entity has at least one secondary language present or used in its immediate vicinity or surrounding context.
  • D. hasLanguageOfSurroundingCountries
    Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
  • E. hasPrimaryLanguage1
    Indicates that an entity’s main or most commonly used language is the specified language.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3496bda8c8190bfc8fade9d1b791c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a018c6b7178819097d5450a1e3c2408 completed May 11, 2026, 7:59 a.m.
PD Predicate disambiguation batch_6a018a4f741c8190babe721a908e2f5e completed May 11, 2026, 7:50 a.m.
Created at: May 1, 2026, 1:35 a.m.